AI Research Internship

United States·Sunnyvaleentry

Data ScienceOtherAi Research Internship

4 views0 saves0 applied

Apply Now

Quick Summary

Overview

About the Institute of Foundation Models We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy.

Key Responsibilities

This intensive, short-term internship offers a unique opportunity for aspiring AI engineers to; • Collect, prepare and processing training and validation datasets. • Assist in designing and tweaking model architectures.

Technical Tools

deep-learning

About the Institute of Foundation Models

We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy.

As part of our team, you’ll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers.

Key Responsibilities

This intensive, short-term internship offers a unique opportunity for aspiring AI engineers to;

• Collect, prepare and processing training and validation datasets.

• Assist in designing and tweaking model architectures.

• Implement testing frameworks to assess model performance.

• Analyze model outputs for accuracy and bias.

• Participate in the review and refinement of AI algorithms.

• Document findings and procedures for team collaboration.

Academic Qualifications

Currently pursuing or recently completed a Master's, or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Applied Mathematics, Statistics, or a related quantitative field.